LANDSAT BIG DATA ANALYSIS FOR DETECTING LONG-TERM WATER QUALITY CHANGES: A CASE STUDY IN THE HAN RIVER, SOUTH KOREA
| Autor: | J. C. Seong, C. S. Hwang, R. Gibbs, K. Roh, M. R. Mehdi, C. Oh, J. J. Jeong |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: | |
| Zdroj: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol IV-1-W1, Pp 83-89 (2017) |
| Druh dokumentu: | article |
| ISSN: | 2194-9042 2194-9050 |
| DOI: | 10.5194/isprs-annals-IV-1-W1-83-2017 |
| Popis: | Landsat imagery satisfies the characteristics of big data because of its massive data archive since 1972, continuous temporal updates, and various spatial resolutions from different sensors. As a case study of Landsat big data analysis, a total of 776 Landsat scenes were analyzed that cover a part of the Han River in South Korea. A total of eleven sample datasets was taken at the upstream, mid-stream and downstream along the Han River. This research aimed at analyzing locational variance of reflectance, analyzing seasonal difference, finding long-term changes, and modeling algal amount change. There were distinctive reflectance differences among the downstream, mid-stream and upstream areas. Red, green, blue and near-infrared reflectance values decreased significantly toward the upstream. Results also showed that reflectance values are significantly associated with the seasonal factor. In the case of long-term trends, reflectance values have slightly increased in the downstream, while decreased slightly in the mid-stream and upstream. The modeling of chlorophyll-a and Secchi disk depth imply that water clarity has decreased over time while chlorophyll-a amounts have decreased. The decreasing water clarity seems to be attributed to other reasons than chlorophyll-a. |
| Databáze: | Directory of Open Access Journals |
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